11687783

L2-Nonexpansive Neural Networks

PublishedJune 27, 2023
Assigneenot available in USPTO data we have
Technical Abstract

Patent Claims
9 claims

Legal claims defining the scope of protection, as filed with the USPTO.

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2. The method of claim 1, wherein a penalty is added when a value of a computed matrix in the training is greater than one, where one is an integer.

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3. The method of claim 1, wherein the non-linear function of the multi-sided ReLU comprises a non-expansive and monotonically increasing scalar function.

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7. The method of claim 1, embodied in a cloud-computing environment.

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9. The computer program product of claim 8, wherein a penalty is added when a value of a computed matrix in the training is greater than one, where one is an integer.

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10. The computer program product of claim 8, wherein the non-linear function of the multi-sided RELU comprises a non-expansive and monotonically increasing scalar function.

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15. The system of claim 14, wherein a penalty is added when a value of a computed matrix in the training is greater than one, where one is an integer.

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16. The system of claim 14, wherein the non-linear function of the multi-sided ReLU comprises a non-expansive and monotonically increasing scalar function.

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17. The system of claim 14, wherein the norm-pooling comprises determining an L2-norm of a max value inside a pooling window.

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20. The system of claim 14, embodied in a cloud-computing environment.

Patent Metadata

Filing Date

Unknown

Publication Date

June 27, 2023

Inventors

Haifeng Qian
Mark Wegman

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Cite as: Patentable. “L2-NONEXPANSIVE NEURAL NETWORKS” (11687783). https://patentable.app/patents/11687783

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